Image cropping process

ABSTRACT

An image cropping process of a multifunction peripheral is provided. Firstly, a top edge endpoint of an object image is searched from a band image of an original image. Then, each band image of the original image is read to search the object endpoint coordinate of a to-be-printed object image zone. The object image zone is outputted to be printed. The image cropping process further provides a strategy for detecting spots in order to enhance the accuracy of searching the object image.

FIELD OF THE INVENTION

The present invention relates to an image cropping process, and moreparticularly to an image cropping process for use in an image processingmethod of a multifunction peripheral.

BACKGROUND OF THE INVENTION

A multifunction peripheral is a device that performs a variety offunctions of a scanner, a copier and a printer. Nowadays, multifunctionperipherals become essential electronic devices for most enterprises orindividual users. FIG. 1 schematically illustrates a process ofperforming a printing operation in a multifunction peripheral accordingto the prior art. Conventionally, for printing a document (e.g. a photo)by the multifunction peripheral, the photo 1 is firstly placed on ascanning window 2. Then, a scanning module within the multifunctionperipheral is moved in a scanning direction Y to scan the photo 1. Thescanned image data are successively stored into the dynamic memorywithin the multifunction peripheral on a line image basis. The lineimage 3 comprises plural pixels 4, which are arranged in a line. Afterseveral line images 3 stored in the dynamic memory are accumulated as aband image 5, the multifunction peripheral performs an image processingoperation on the basis of a single band image 5. Then, plural processedband images 5 are combined as an original image 6, which is transmittedto the multifunction peripheral on a band image basis to be printed out.

Moreover, in a case that the document to be printed has a small imageportion, the user may hope only the image portion is scanned because itis time-saving for the multifunction peripheral to scan only the imageportion. As shown in FIG. 1, the original image 6 comprises an objectimage 7 and the rest of the object image 7 (i.e. a blank image). Foracquiring only the object image 7, the multifunction peripheral usuallyprovides an image cropping process. That is, before the scanningoperation is done, a pre-scanning operation is performed to quickly scanthe document at a low resolution. By performing the pre-scanningoperation, the object image size of the original image and the desiredscanning position can be recognized. After the actual range of theobject image to be scanned is reset, the regular scanning operation willbe done.

The pre-scanning operation used in the image cropping process, however,still has some drawbacks. For example, even if the area of the objectimage to be scanned is very small, the time for performing thepre-scanning operation is needed. For example, if a multifunctionperipheral having an A3-sized scanning window is used to scan a 3×5photo, the conventional image cropping process needs to firstly scan theA3-sized scanning window. After the position of the photo is recognizedby an algorithm, the scanning range is reset and then the scanningoperation is performed. Moreover, since the dynamic memory of theordinary multifunction peripheral has a limited capacity, the originaldata produced by the pre-scanning operation need to be stored in thedynamic memory of the multifunction peripheral. The image data comprisethe scanning data of the image zone and the data of the blank zone.Since the image data occupy a large portion of the dynamic memory, theimage processing speed of the multifunction peripheral is impaired.

From the above discussions, the conventional image cropping process istime-consuming. Regardless of the object image size, a pre-scanningcycle is required and a large portion of the dynamic memory is occupied.

SUMMARY OF THE INVENTION

The present invention provides an image cropping process for cropping animage at a high processing speed.

The present invention also provides an image cropping process forreducing the occupancy of the dynamic memory of the multifunctionperipheral.

In accordance with an aspect of the present invention, there is providedan image cropping process of a multifunction peripheral. Themultifunction peripheral is configured to scan a document to acquire anoriginal image and print the original image. The original image includesan object image. The original image is segmented into plural bandimages. Each of the band images includes plural line images.

The image cropping process includes steps of: (A) reading a band imageof the original image; (B) judging whether a top edge endpointcoordinate of the object image is included in the read band image bysub-steps of: (B1) searching a first line image containing the objectimage from the read band image, and calculating two object endpointcoordinates of the first line image containing the object image; (B2)successively judging whether all of next plural line images of the firstline image contain the two object endpoint coordinates; (B3) judgingwhether a width between two object endpoint coordinates of at least oneline image of the next plural line images is greater than a preset widthvalue, wherein if all of the judging conditions of the steps (B1), (B2)and (B3) are satisfied, each of the two object endpoint coordinates ofthe first line image is determined as the top edge endpoint coordinate,wherein if one of the judging conditions of the steps (B1), (B2) and(B3) is unsatisfied, the steps (A) and (B) are repeatedly performeduntil the top edge endpoint coordinate is determined; (C) calculatingobject endpoint coordinates of all line images following the plural lineimages of the band image; (D) outputting the object endpoint coordinatehaving the minimum X-axis coordinate value and the object endpointcoordinate having the maximum X-axis coordinate value among all objectendpoint coordinates of the band image; (E) receiving the objectendpoint coordinates outputted in the step (D) for further performing aprinting processing operation; (F) reading a next band image, andsearching all object endpoint coordinates of all line images of the nextband image; (G) outputting the object endpoint coordinate having theminimum X-axis coordinate value and the object endpoint coordinatehaving the maximum X-axis coordinate value among all object endpointcoordinates of the next band image; (H) receiving the object endpointcoordinates outputted in the step (H) for performing the furtherprinting processing operation; and (I) repeatedly performing the steps(F), (G) and (H).

In an embodiment, the step (B1) includes sub-steps of: (B1-1) reading aline image of the band image, and performing a Gamma correction on theline image, wherein the line image comprises plural pixels; (B1-2)judging whether the pixels of the line image contain the object image byhorizontally scaling down the line image at a magnification to acquire ascaled-down line image, comparing grayscale values of respective pixelsof the scaled-down line image with a grayscale threshold value todetermine the pixel whose grayscale value is lower than the grayscalethreshold value as an object pixel, and recording coordinates values ofa leftmost object pixel and a rightmost object pixel of the objectpixels of the scaled-down line image; and (B1-3) performing a pixelcoordinate transformation by respectively transforming the coordinatesvalues of the leftmost object pixel and the rightmost object pixel ofthe object pixels of the scaled-down line image into coordinates valuesof a leftmost object pixel and a rightmost object pixel of the objectpixels of the line image, and recording the coordinates values of theleftmost object pixel and the rightmost object pixel of the objectpixels of the line image as the two object endpoint coordinates.

In an embodiment, the grayscale threshold value W(n+1) is calculated bythe following equation: W(n+1)=W(n)+(W(n+1)max−W(n))/T, where, n=0, 1,2, . . . , (A-1), W(0) is an initial grayscale value, W(n) is anaccumulated reference grayscale value of the n^(th) line image,W(n+1)max indicates the maximum grayscale value among all pixels of the(n+1)^(th) scaled-down line image that is obtained by horizontallyscaling down the (n+1)^(th) line image at a magnification, and T and Aare positive integers.

In an embodiment, if W(n+1)max is higher than W(n), T=Td, and ifW(n+1)max is lower than W(n), T=Tu, wherein Tu and Td are differentpositive integers.

In an embodiment, the step (B1) includes sub-steps of: (B1-1) reading aline image of the band image, and performing a Gamma correction on theline image, wherein the line image comprises plural pixels; (B1-2)judging whether the pixels of the line image contain the object imageby: horizontally scaling down the line image at a first magnification toacquire a first scaled-down line image; comparing grayscale values ofrespective pixels of the first scaled-down line image with a grayscalethreshold value to determine the pixel whose grayscale value is lowerthan the grayscale threshold value as a would-be object pixel, andrecording coordinates values of a leftmost would-be object pixel and arightmost would-be object pixel of the would-be object pixels of thefirst scaled-down line image; subtracting a predetermined value from aX-axis coordinate value of the leftmost would-be object pixel of thefirst scaled-down line image to acquire a left reference coordinate, andadding the predetermined value to a X-axis coordinate value of therightmost would-be object pixel to acquire a right reference coordinate;respectively transforming the left reference coordinate and the rightreference coordinate into a leftmost reference coordinate and arightmost reference coordinate of the line image, horizontally scalingdown the line image between the leftmost reference coordinate and therightmost reference coordinate at a second magnification to acquire asecond scaled-down line image, comparing grayscale values of respectivepixels of the second scaled-down line image with the grayscale thresholdvalue to determine the pixel whose grayscale value is lower than thegrayscale threshold value as an object pixel, and recording coordinatesvalues of a leftmost object pixel and a rightmost object pixel of thesecond scaled-down line image, wherein the second magnification isgreater than the first magnification; and (B1-3) performing a pixelcoordinate transformation by respectively transforming the coordinatesvalues of the leftmost object pixel and the rightmost object pixel ofthe second scaled-down line image into coordinates values of a leftmostobject pixel and a rightmost object pixel of the object pixels of theline image, and recording the coordinates values of the leftmost objectpixel and the rightmost object pixel of the object pixels of the lineimage as the two object endpoint coordinates.

In an embodiment, the grayscale threshold value W(n+1) is calculated bythe following equation: W(n+1)=W(n)+(W(n+1)max−W(n))/T, where, n=0, 1,2, . . . , (A-1), W(0) is an initial grayscale value, W(n) is anaccumulated reference grayscale value of the n^(th) line image,W(n+1)max indicates the maximum grayscale value among all pixels of the(n+1)^(th) scaled-down line image that is obtained by horizontallyscaling down the (n+1)^(th) line image at a magnification, and T and Aare positive integers.

In an embodiment, if W(n+1)max is higher than W(n), T=Td, and ifW(n+1)max is lower than W(n), T=Tu, wherein Tu and Td are differentpositive integers.

In an embodiment, the step (F) includes sub-steps of: (F-1) reading aline image of the next band image, and performing a Gamma correction onthe line image, wherein the line image comprises plural pixels; (F-2)judging whether the pixels of the line image contain the object image byhorizontally scaling down the line image at a magnification to acquire ascaled-down line image, comparing grayscale values of respective pixelsof the scaled-down line image with a grayscale threshold value todetermine the pixel whose grayscale value is lower than the grayscalethreshold value as an object pixel, and recording coordinates values ofa leftmost object pixel and a rightmost object pixel of the objectpixels of the scaled-down line image; and (F-3) performing a pixelcoordinate transformation by respectively transforming the coordinatesvalues of the leftmost object pixel and the rightmost object pixel ofthe object pixels of the scaled-down line image into coordinates valuesof a leftmost object pixel and a rightmost object pixel of the objectpixels of the line image, and recording the coordinates values of theleftmost object pixel and the rightmost object pixel of the objectpixels of the line image as the two object endpoint coordinates.

In an embodiment, the grayscale threshold value W(n+1) is calculated bythe following equation: W(n+1)=W(n)+(W(n+1)max−W(n))/T, where, n=0, 1,2, . . . , (A-1), W(0) is an initial grayscale value, W(n) is anaccumulated reference grayscale value of the n^(th) line image,W(n+1)max indicates the maximum grayscale value among all pixels of the(n+1)^(th) scaled-down line image that is obtained by horizontallyscaling down the (n+1)^(th) line image at a magnification, and T and Aare positive integers.

In an embodiment, if W(n+1)max is higher than W(n), T=Td, and ifW(n+1)max is lower than W(n), T=Tu, wherein Tu and Td are differentpositive integers.

In an embodiment, the step (F) includes sub-steps of: (F-1) reading aline image of the next band image, and performing a Gamma correction onthe line image, wherein the line image comprises plural pixels; (F-2)judging whether the pixels of the line image contain the object imageby: horizontally scaling down the line image at a first magnification toacquire a first scaled-down line image; comparing grayscale values ofrespective pixels of the first scaled-down line image with a grayscalethreshold value to determine the pixel whose grayscale value is lowerthan the grayscale threshold value as a would-be object pixel, andrecording coordinates values of a leftmost would-be object pixel and arightmost would-be object pixel of the would-be object pixels of thefirst scaled-down line image; subtracting a predetermined value from aX-axis coordinate value of the leftmost would-be object pixel of thefirst scaled-down line image to acquire a left reference coordinate, andadding the predetermined value to a X-axis coordinate value of therightmost would-be object pixel to acquire a right reference coordinate;and respectively transforming the left reference coordinate and theright reference coordinate into a leftmost reference coordinate and arightmost reference coordinate of the line image, horizontally scalingdown the line image between the leftmost reference coordinate and therightmost reference coordinate at a second magnification to acquire asecond scaled-down line image, comparing grayscale values of respectivepixels of the second scaled-down line image with the grayscale thresholdvalue to determine the pixel whose grayscale value is lower than thegrayscale threshold value as an object pixel, and recording coordinatesvalues of a leftmost object pixel and a rightmost object pixel of thesecond scaled-down line image, wherein the second magnification isgreater than the first magnification; and (B1-3) performing a pixelcoordinate transformation by respectively transforming the coordinatesvalues of the leftmost object pixel and the rightmost object pixel ofthe second scaled-down line image into coordinates values of a leftmostobject pixel and a rightmost object pixel of the object pixels of theline image, and recording the coordinates values of the leftmost objectpixel and the rightmost object pixel of the object pixels of the lineimage as the two object endpoint coordinates.

In an embodiment, the grayscale threshold value W(n+1) is calculated bythe following equation: W(n+1)=W(n)+(W(n+1)max−W(n))/T, where, n=0, 1,2, . . . , (A-1), W(0) is an initial grayscale value, W(n) is anaccumulated reference grayscale value of the n^(th) line image,W(n+1)max indicates the maximum grayscale value among all pixels of the(n+1)^(th) scaled-down line image that is obtained by horizontallyscaling down the n^(th) line image at a magnification, and T and A arepositive integers.

In an embodiment, if W(n+1)max is higher than W(n), T=Td, and ifW(n+1)max is lower than W(n), T=Tu, wherein Tu and Td are differentpositive integers.

The above objects and advantages of the present invention will becomemore readily apparent to those ordinarily skilled in the art afterreviewing the following detailed description and accompanying drawings,in which:

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically illustrates a process of performing a printingoperation in a multifunction peripheral according to the prior art;

FIG. 2 is a flowchart illustrating an image processing method of amultifunction peripheral according to an embodiment of the presentinvention, in which the image processing method includes an imagecropping process;

FIG. 3 is a flowchart illustrating an image cropping process accordingto an embodiment of the present invention;

FIG. 4 schematically illustrates the definitions of an original image,an object image and a band image used in the image cropping process ofthe present invention;

FIG. 5A schematically illustrates a portion of the first band image ofthe original image;

FIG. 5B schematically illustrates a way of judging whether an objectpixel is included in the first band image;

FIG. 6A schematically illustrates a portion of a second band image ofthe original image;

FIGS. 6B and 6C schematically illustrate a way of judging whether anobject pixel is included in the second band image;

FIG. 7A schematically illustrates a portion of a third band image of theoriginal image;

FIG. 7B schematically illustrates a way of cropping the third band imageto acquire an object image zone;

FIG. 8A schematically illustrates a portion of a fourth band image ofthe original image;

FIG. 8B schematically illustrates a way of judging whether an objectpixel is included in the fourth band image;

FIG. 8C schematically illustrates a way of cropping the third band imageto acquire an object image zone;

FIG. 9 schematically illustrates the object image zones acquired by theimage cropping process of the present invention; and

FIG. 10 schematically illustrates a process of judging whether theplural line images contain object pixels according to another embodimentof the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

For obviating the drawbacks encountered from the prior art, the presentinvention provides an image cropping process for use in an imageprocessing method of a multifunction peripheral. By the image croppingprocess of the present invention, an object image is cropped from theoriginal image in real time during a printing operation is performed bythe multifunction peripheral and an image processing method isimplemented. As a consequence, the printing speed is enhanced.

FIG. 2 is a flowchart illustrating an image processing method of amultifunction peripheral according to an embodiment of the presentinvention, in which the image processing method includes an imagecropping process. The image processing method 100 comprises thefollowing steps. Firstly, band images of an original image are inputted(Step S101). Then, an image brightness calibration process is performed(Step S102), and a color coordinate transformation is performed (StepS103). Then, a background elimination process is performed (Step S104).Then, Step S105 is performed to enhance the image sharpness and thesmoothness. Then, an image cropping process is performed (Step S106),and a chromaticity coordinate transformation is performed (Step S107).After the image size is adjusted (Step S108) and a halftone processingprocess is done (Step S109), the processed image is printed (Step S110).

In accordance with a key feature of the present invention, the objectimage is cropped from the original image when the image processingmethod is implemented. That is, the present invention is aimed at thestep S106 of performing the image cropping process. The other steps ofthe image processing method 100 are well known in the art, and are notredundantly described herein. Hereinafter, the step S106 of performingthe image cropping process will be illustrated in more detail withreference to FIG. 3.

FIG. 3 is a flowchart illustrating an image cropping process accordingto an embodiment of the present invention. Firstly, a band image is read(Step S 10). Then, Step S20 is performed to judge whether a top edgeendpoint of the object image is included in the read band image. If thejudging condition is satisfied, Step S30 is performed. Whereas, if thejudging condition is unsatisfied, Step S10 is repeatedly done until thetop edge endpoint of the object image is included in any other read bandimage. In Step S30, the object endpoint coordinates of all images linesof the band image having the top edge endpoint are calculated. In StepS40, among all object endpoint coordinates of the band image having thetop edge endpoint, the object endpoint coordinate having the minimumX-axis coordinate value and the object endpoint coordinate having themaximum X-axis coordinate value are outputted for further performing aprinting processing operation. Then, a next band image is read (StepS50), and all object endpoint coordinates of all line images of the nextband image are calculated (Step S60). Then, Step S70 is performed tojudge whether no object image is contained in successive plural lineimages. If the judging condition is satisfied, Step S90 is performed.Whereas, if the judging condition is unsatisfied, Step S80 is performed.In Step S80, among all object endpoint coordinates of the band image,the object endpoint coordinate having the minimum X-axis coordinatevalue and the object endpoint coordinate having the maximum X-axiscoordinate value are outputted for further performing a printingprocessing operation. In Step S90, among all object endpoint coordinatesof the band image, the object endpoint coordinate having the minimumX-axis coordinate value and the object endpoint coordinate having themaximum X-axis coordinate value are outputted for further performing aprinting processing operation. After Step S90 is done, the imagecropping process is completed.

Hereinafter, the steps of the image cropping process as shown in FIG. 3will be illustrated in more details.

FIG. 4 schematically illustrates the definitions of an original image,an object image and a band image used in the image cropping process ofthe present invention. The original image 201 denotes the image havingthe same size as the printed paper (e.g. an A4-sized paper). The objectimage denotes the image of the document to be printed (e.g. an A6-sizedphoto). The original image 201 is segmented into plural identical-sizedband image portions. For brevity, only a first band image 203, a secondband image 204, a third band image 205 and a fourth band image 206 areindicated in the drawing.

Hereinafter, the detailed contents of the first band image 203 of theoriginal image 201 will be illustrated with reference to FIG. 5A. Asshown in FIG. 5A, the first band image 203 comprises plural line images2030, 2031, 2032, . . . , and so on. Each line image comprises pluralpixels. The background pixels (i.e. the pixels of the non-object image)are indicated by hollow circles. The pixels of the object image or thepixels of the spot's image are indicated by solid circles (see FIG. 6A).

For judging whether a top edge endpoint of the object image is includedin the first read band image 203, it is necessary to judge whether theplural line images of the first read band image 203 contains the objectpixels or not. The object pixels denote the pixels of the object image.The rest of the object pixels are referred as background pixels.

For judging whether a pixel is an object pixel, a preset grayscale valueand a grayscale threshold value are defined. The preset grayscale valueis set by the manufacturer. The grayscale threshold value is determinedby the following approach.

The grayscale threshold value is obtained by calculating the grayscalevalues of the pixels of plural gamma-corrected line images of the bandimage. The grayscale threshold value denotes a reference grayscale valueof the background pixel. That is, the pixel whose grayscale value ishigher than the grayscale threshold value is determined as thebackground pixel, but the pixel whose grayscale value is lower than thegrayscale threshold value is determined as the object pixel. The numberof line images to be used for calculating the grayscale threshold valuemay be predetermined by the manufacturer.

For example, as shown in FIG. 5A, if the three line images 2030, 2031and 2032 of the first band image 203 are used for calculating thegrayscale threshold value, the line images 2030, 2031 and 2032 of thefirst band image 203 are successively read. Before the calculation ofthe grayscale threshold value, the line images 2030, 2031 and 2032 aregamma-corrected. The gamma correction technique is well known in theart, and is not redundantly described herein.

Then, as shown in FIG. 5B, the gamma-corrected first line image 2030 ishorizontally scaled down at a magnification (e.g. 1/64). After thegamma-corrected first line image 2030 is horizontally scaled down at themagnification of 1/64, a scaled-down first line image 20301 is acquired.In this situation, the arithmetic mean of the grayscale values of every64 pixels of the first line image 2030 is calculated as a grayscalevalue of the scaled-down first line image 20301. For example, if thefirst line image 2030 originally has 6,400 pixels, after the first lineimage 2030 is horizontally scaled down at the magnification of 1/64, thescaled-down first line image 20301 has 100 grayscale values. Then, themaximum grayscale value among all pixels of the scaled-down first lineimage 20301 is recorded.

In an embodiment, the grayscale threshold value W(n+1) is calculated bythe following equation:W(n+1)=W(n)+(W(n+1)max−W(n) )/T

In the above equation, W(n) is an accumulated reference grayscale valueof the n^(th) line image, W(n+1)max indicates the maximum grayscalevalue among all pixels of the (n+1)^(th) scaled-down line image that isobtained by horizontally scaling down the (n+1)^(th) line image at amagnification, and T is a positive integer. If W(n+1)max is higher thanW(n), T=Td. Whereas, if W(n+1)max is lower than W(n), T=Tu. Tu and Tdare different preset positive integers. The value (n+1) is the number ofline images to be used for calculating the grayscale threshold value. Inthis embodiment, since three line images are used for calculating thegrayscale threshold value, n=0, 1, 2. If n=0, W(n)=W(0)=preset grayscalevalue.

The accumulated reference grayscale value of the first line image W(1)may be obtained by the equation: W(1)=W(0)+(W(1)max−W(0))/T. Since W(0),W(1)max and T are known, the accumulated reference grayscale value W(1)of the first line image will be calculated.

Next, the gamma-corrected second line image 2031 is also horizontallyscaled down at the magnification of 1/64. In addition, the maximumgrayscale value among all pixels of the scaled-down second line image(not shown) is recorded. Since the accumulated reference grayscale valueW(1) of the first line image 2030 and the maximum grayscale value amongall pixels of the scaled-down first line image 20301 are known, theaccumulated reference grayscale value W(2) of the second line image isobtained according to the above equation.

Next, the gamma-corrected third line image 2032 is also horizontallyscaled down at the magnification of 1/64. In addition, the maximumgrayscale value among all pixels of the scaled-down third line image(not shown) is recorded. Similarly, the accumulated reference grayscalevalue W(3) of the third line image is obtained according to the aboveequation. The accumulated reference grayscale value W(3) is thegrayscale threshold value determined by the manufacturer according tothe three line images. It is noted that the grayscale threshold value ofthe printed image may be calculated in every printing cycle.

After the grayscale threshold value is acquired, it is necessary tojudge whether the first line image 2030 of the first band image 203contains any object pixel. The line image 2030 is firstly read. Sincethe line images 2030, 2031 and 2032 have been gamma-corrected during theprocessing of determining the grayscale threshold value, it is notnecessary to repeatedly perform the gamma correction on the line images2030, 2031 and 2032 during the process of judging the object pixels.Since the remaindering line images have not been gamma-corrected, theymust be gamma-corrected in the further processing step.

Please refer to FIG. 5B again. After the gamma-corrected first lineimage 2030 is read, the gamma-corrected first line image 2030 ishorizontally scaled down at a magnification (e.g. 1/64) to acquire ascaled-down first line image 20301. As mentioned above, if the firstline image 2030 originally has 6,400 pixels, after the first line image2030 is horizontally scaled down at the magnification of 1/64, thescaled-down first line image 20301 has 100 grayscale values. Then, thegrayscale values of the 100 pixels of the scaled-down first line image20301 are successively compared with the grayscale threshold value. Thepixels whose grayscale values are higher than the grayscale thresholdvalue are determined as the background pixels. Whereas, the pixels whosegrayscale values are lower than the grayscale threshold value aredetermined as the object pixels.

In accordance with the present invention, the way of judging whether thepixels are object pixels is performed by comparing the grayscale valuesof all pixels of the scaled-down line image with the grayscale thresholdvalue. Since the line image is horizontally scaled down to acquire thescaled-down line image, the amount of grayscale values for comparisonwill be reduced. In this situation, the computing time of themultifunction peripheral will be reduced.

Next, among the object pixels of the scaled-down line image 20301, thecoordinate value of the leftmost object pixel and the coordinate valueof the rightmost object pixel are recorded. Then, the coordinate valuesof the leftmost object pixel and the rightmost object pixel of thescaled-down line image 20301 are respectively restored to the coordinatevalues of the leftmost object pixel and the rightmost object pixel ofthe line image 2030. Take the band image 203 as shown in FIG. 5 forexample. Since the line images 2030, 2031, 2032 and other line imagesincluded in the band image 203 are non-object image, it means that thepixels of these line images are background pixels. In this situation,the grayscale values of all pixels of each scaled-down line image (e.g.the scaled-down line image 20301) are all higher than the grayscalethreshold value. The process of restoring the coordinate values of thescaled-down line image to the coordinate values of the original lineimage will be illustrated later.

Since all of the line images includes in the first band image 203 do notcontain the object pixels, no top edge endpoints are included in thefirst band image 203. Next, the next band image 204 is read, and thestep S20 is performed to judge whether a top edge endpoint of the objectimage is included in the band image 204.

Hereinafter, a way of judging whether an object pixel is included in thesecond band image 204 will be illustrated with reference to FIGS. 6A, 6Band 6C. As shown in FIG. 6A, the second band image 204 comprises pluralline images 2040, 2041, 2042, 2043, 2044, . . . , and so on. The threeline images 2041, 2042 and 2043 are indicated by solid circles becausethey contain image information.

Firstly, an approach of judging whether the second band image 204includes an object pixel is performed. The way of searching the objectpixels of all line images of the second band image 204 is similar to theway of judging the first band image 203. As shown in FIG. 6B, the firstline image 2040 of the second band image 204 is horizontally scaled downat a magnification (e.g. 1/64) to acquire a scaled-down first line image20401. Then, the grayscale values of the 100 pixels of the scaled-downfirst line image 20401 are successively compared with the grayscalethreshold value. The pixels whose grayscale values are lower than thegrayscale threshold value are determined as the object pixels. Sincenone of the pixels of the scaled-down first line image 20401 are lowerthan the grayscale threshold value, all of the pixels of the first lineimage 2040 are background pixels.

Please refer to FIG. 6C. Then, the next line image 2041 is read, andhorizontally scaled down to acquire a scaled-down line image 20411.Then, the grayscale values of all pixels of the scaled-down line image20411 are successively compared with the grayscale threshold value. Asshown in FIG. 6C, the scaled-down line image 20411 includes some objectpixels (i.e. the pixels indicated by solid circles). That is, pixelsindicated by the solid circles are pixels whose grayscale values arelower than the grayscale threshold value. After all of the object pixelsof the scaled-down line image 20411 are acquired, the coordinate value(X₁, Y) of the leftmost object pixel and the coordinate value (X₂, Y) ofthe rightmost object pixel of the scaled-down line image 20411 arerecorded.

Next, the coordinate value (X₁, Y) of the leftmost object pixel and thecoordinate value (X₂, Y) of the rightmost object pixel of thescaled-down line image 20411 are respectively converted into thecoordinate value I₁ of the leftmost object pixel and the coordinatevalue I₂ of the rightmost object pixel of the line image 2041 accordingto the following formulae: I₁−(64×(X₁+1/2), Y), and I₂=(64×(X₂+1/2), Y).

Then, the coordinate value I₁ of the leftmost object pixel and thecoordinate value I₂ of the rightmost object pixel of the line image 2041are recorded.

Next, the steps of judging whether the remaindering line imagesfollowing the first line image 2041 (e.g. the three line images 2042,2043 and 2044 following the first line image 2041) contain object pixelsare successively performed. If any of the three line images 2042, 2043and 2044 contains the object pixels, the coordinate values of theleftmost object pixel and the rightmost object pixel of such line imageare recorded.

Optionally, the step of judging whether a top edge endpoint of theobject image is included in the read band image further includes a spotdetecting process. As shown in FIG. 6A, the line images 2041, 2042 and2043 are line images with object pixels, but on object pixels areincluded in the line image 2044. In accordance with the presentinvention, after the line image with the object pixels is firstlydetected, it is necessary to judge whether the three line imagesfollowing the first line image 2041 contain object pixels. In the bandimage 204 of FIG. 6A, not all of the three line images 2042, 2043 and2044 following the first line image 2041 contain the object pixels. Thatis, only the two line image 2042 and 2043 contain the object pixels, butno object pixels are included in the line image 2044. In this situation,it is determined that the first line image 2041 does not contain the topedge endpoint. On the other hand, the object pixels included in the lineimages 2041, 2042 and 2043 are considered as spots and neglected.

In FIG. 7A, a portion of a next band image 205 is shown. Since no topedge endpoint of the object image is included in the band images 203 and204, the next band image 205 is read to judge whether a top edgeendpoint of the object image is included in the band image 205.

As shown in FIG. 7A, the line image 2051 of the band image 205 containsobject pixels. By the above-mentioned procedure of acquiring thecoordinate values of the leftmost object pixel and the rightmost objectpixel, the coordinate value I₃ of the leftmost object pixel and thecoordinate value I₄ of the rightmost object pixel of the line image 2051are acquired. For judging whether the object pixels of the line image2051 are spots, it is necessary to judge whether the next three lineimages of the first line image 2051 contain object pixels. As shown inFIG. 7A, all of the next three line images 2052, 2053 and 2054 of thefirst line image 2051 contain the object pixels. Consequently, thecoordinate values I₅ and I₆ of the two endpoint object pixels of theline image 2052, the coordinate values I₇ and I₈ of the two endpointobject pixels of the line image 2053 and the coordinate values I₉ andI₁₀ of the two endpoint object pixels of the line image 2054 aresuccessively recorded.

For precisely judging whether the object image is a spot, it isnecessary to judge whether all of the next plural line images of thefirst object-pixel-containing line image contain object pixels. Inaddition, the present invention further provides a spot detectingprocess for judging whether the detected object image is a spot. Thespot detecting process is performed to judging whether the width betweenthe coordinate values of two endpoint object pixels of at least one lineimage of the next plural line images is greater than a preset widthvalue (e.g. 6 pixel width). As shown in FIG. 7A, the width W₁ betweenthe coordinate values I₉ and I₁₀ of the two endpoint object pixels ofthe line image 2054 is greater than the preset width value (e.g. 6 pixelwidth), the object pixels included in the line images 2051, 2052, 2053and 2054 are not spots' images. In this situation, the coordinate valuesI₃ and I₄ of the two endpoint object pixels of the line image 2051 arethe coordinate values of the top edge endpoint of the object images.

The strategy of judging whether the object pixels are spots will beillustrated as follows. Generally, the image information of the objectimage is usually continuous and widespread, but the image information ofthe spot is usually discontinuous and has a narrow scope. If the objectpixel of the first line image is really at the top edge of the objectimage, the plural successive line image following the top edge of theobject image may contain the object pixels with the image information ofthe object image. Moreover, the width between the coordinate values oftwo endpoint object pixels denotes a scope of the object image. That is,by judging whether the plural successive line image contain the objectpixels, and then judging whether the width between the coordinate valuesof two endpoint object pixels of at least one line image is greater thanthe preset width value, the detected object pixels may be determined aseither the top edge of the object image or the spots.

After the line image 2051 is determined as the top edge of the objectimage, the coordinate values of respective two endpoint object pixels ofthe line images following the line image 2054 of the third band image205 are successively calculated. In addition, the coordinate values ofrespective two endpoint object pixels of these line images are recordeduntil the last line images 2055 of the third band image 205 arerecorded. As shown in FIG. 7A, the two endpoint object pixels of thelast line image 2055 has coordinate values I₁₁ and I₁₂.

Next, among the endpoint object pixels of the third band image 205, theendpoint object pixel having the minimum X-axis coordinate value and theendpoint object pixel having the maximum X-axis coordinate value areoutputted. For example, as shown in FIG. 7A, the coordinate values ofthe endpoint object pixels of the third band image 205 comprise thecoordinate values I₃ and I₄ of the two endpoint object pixels of theline image 2051, the coordinate values I₅ and I₆ of the two endpointobject pixels of the line image 2052, the coordinate values I₅ and I₆ ofthe two endpoint object pixels of the line image 2052, the coordinatevalues I₇ and I₈ of the two endpoint object pixels of the line image2053 and the coordinate values I₉ and I₁₀ of the two endpoint objectpixels of the line image 2054, . . . , and the coordinate values I₁₁ andI₁₂ of the two endpoint object pixels of the last line image 2055. Thecoordinate values of the endpoint object pixel having the minimum X-axiscoordinate value and the endpoint object pixel having the maximum X-axiscoordinate value are respectively the coordinate values I₁₁ and I₁₂ ofthe two endpoint object pixels of the last line image 2055. Please referto FIG. 7B. According to the coordinate value I₁₁ of the endpoint objectpixel having the minimum X-axis coordinate value and the coordinatevalue I₁₂ of the endpoint object pixel having the maximum X-axiscoordinate value, a Y-direction cropping operation is performed on thethird band image 205 to acquire an object image zone 205′. Then, theobject image zone 205′ is further processed by the remaindering steps ofthe image processing method, including the chromaticity coordinatetransformation (Step S107), the image size adjustment (Step S108), thehalftone processing procedure (Step S109) and the printing procedure(Step S110).

After the third band image 205 is processed, a fourth band image 206 issuccessively read. Hereinafter, a way of processing the fourth bandimage 206 will be illustrated with reference to FIGS. 8A, 8B and 8C. Asshown in FIG. 8A, the fourth band image 206 comprises plural line images2060, 2061, 2462, 2063, . . . , and so on. Since the endpoint objectpixels have been acquired, it is not necessary to repeatedly perform thestep of detecting the top edge endpoint. Whereas, it is necessary tocalculate the coordinate values of the leftmost object pixel and therightmost object pixel of each line image of the fourth band image 206.

The procedure of calculating the coordinate values of the two endpointobject pixels of each line image of the fourth band image 206 will beillustrated as follows. Similarly, take the line image 2060 for example.The line image 2060 is horizontally scaled down to acquire a scaled-downline image 20601. Then, the coordinate values (X₃, Y) and (X₄, Y) of thetwo endpoint object pixels of the scaled-down line image 20601 arecalculated. Then, the coordinate values (X₃, Y) and (X₄, Y) are restoredto the coordinate system of the line image 2060, so that the coordinatevalues I₁₃ and I₁₄ of the two endpoint object pixels of the line image2060 are acquired. The above procedure is repeatedly performed on theremaindering line images of the band image 206 until the coordinatevalues I₁₅ and I₁₆ of the two endpoint object pixels of the last lineimage 2065 are acquired.

Next, among the endpoint object pixels of the fourth band image 206, theendpoint object pixel having the minimum X-axis coordinate value and theendpoint object pixel having the maximum X-axis coordinate value areoutputted. As shown in FIG. 8A, among the endpoint object pixels of thefourth band image 206, the coordinate value of the endpoint object pixelhaving the minimum X-axis coordinate value is I₁₅, and the endpointobject pixel having the maximum X-axis coordinate value is I₁₆.According to the coordinate value I₁₅ and I₁₆ a Y-direction croppingoperation is performed on the fourth band image 206 to acquire an objectimage zone 206′. Then, the object image zone 206′ is further processedby the remaindering steps of the image processing method.

The remaindering steps of processing the plural band images followingthe fourth band image 206 are similar to those of processing the fourthband image 206, and are not redundantly described herein.

FIG. 9 schematically illustrates the object image zones acquired by theimage cropping process of the present invention. The object image zones(e.g. 205′ and 206′) are shown with respect to the whole original image201. As shown in FIG. 9, the object image zones (e.g. 205′ and 206′)comprise a majority of the pixels of the object image 202. Thebackground pixels not belonging to the object image are not sent to theprinting module to be printed. As a consequence, the printing speed ofthe multifunction peripheral will be enhanced.

After most band images are processed, if the line image with no objectpixel is detected again, it means that the band images containing theobject pixels may be completely detected and no object image iscontained in a further band image. In other words, if the line imagewith no object pixel is detected again, for example no object pixel isincluded in the successive plural line images, it means that the objectimage has been completely read and the remaindering band images belongto the background image. Meanwhile, the image cropping process is ended,and it is not necessary to process the further band images.Consequently, the printing speed is enhanced.

The present invention further provides another embodiment of detectingthe object pixels. FIG. 10 schematically illustrates a process ofjudging whether the plural line images contain object pixels accordingto another embodiment of the present invention. Take the first lineimage 2060 of the band image 206 for example. In the process ofdetecting the object pixels of this embodiment, the line image ishorizontally scaled down for two times to judge whether the line imagecontains the object pixels. Firstly, the line image 2060 is read. Then,the line image 2060 is gamma-corrected. Then, the gamma-corrected lineimage 2060 is horizontally scaled down at a first magnification (e.g. ⅙)to acquire a first scaled-down line image 20602. Then, the grayscalevalues of all pixels of the first scaled-down line image 20602 aresuccessively compared with a grayscale threshold value. The pixel whosegrayscale value is lower than the grayscale threshold value isdetermined as a would-be object pixel. Then, the coordinate value I₁₇(X₅, Y) of the leftmost would-be object pixel and the coordinate valueI₁₈ (X₆, Y) of the rightmost would-be object pixel of the firstscaled-down line image 20602 are recorded. Meanwhile, the firsthorizontally scaling-down operation is completed. Next, a predeterminedvalue (e.g. three pixels) is subtracted from the coordinate value I₁₇ ofthe leftmost would-be object pixel of the first scaled-down line image20602, thereby acquiring a left reference coordinate I₁₉ (X₅−3, Y). Inaddition, the coordinate value I₁₈ of the rightmost would-be objectpixel of the first scaled-down line image 20602 is added by thepredetermined value, thereby acquiring a right reference coordinate I₂₀(X₆+3, Y). Then, the left reference coordinate I₁₉ and the rightreference coordinate I₂₀ are respectively restored to the leftmostreference coordinate I₁₉′ and the rightmost reference coordinate I₂₀′ ofthe line image 2060. The line image between the leftmost referencecoordinate I₁₉′ and the rightmost reference coordinate I₂₀′ ishorizontally scaled down at a second magnification (e.g. ⅓) to acquire asecond scaled-down line image 20603. Meanwhile, the second horizontallyscaling-down operation is completed. The left endpoint coordinate andthe right endpoint coordinate of the second scaled-down line image 20603are respectively I₁₉″ (6/3×(X₅−3), Y) and I₂₀″ ((6/3×(X₆+3)+(6/3−1)),Y). Then, the grayscale values of all pixels of the second scaled-downline image 20603 are successively compared with the grayscale thresholdvalue. The pixel whose grayscale value is lower than the grayscalethreshold value is determined as an object pixel. Then, the coordinatevalue I₂₁ (X₇, Y) of the leftmost object pixel and the coordinate valueI₂₂ (X₈, Y) of the rightmost object pixel of the second scaled-down lineimage 20603 are recorded. Then, the coordinate value I₂₁ (X₇, Y) of theleftmost object pixel and the coordinate value I₂₂ (X₈, Y) of therightmost object pixel of the second scaled-down line image 20603 arerespectively restored to the leftmost reference coordinate I₂₃(3×(X₇+1/2), Y) and the rightmost reference coordinate I₂₄ (3×(X₈+1/2),Y) of the line image 2060. The leftmost reference coordinate I₂₃ and therightmost reference coordinate I₂₄ of the line image 2060 are recordedas the two object endpoint coordinates.

In this embodiment, two horizontally scaling-down operations may obviatethe possible problems encountered from the single horizontallyscaling-down operation. If the single horizontally scaling-downoperation is performed at a low magnification, the use of the arithmeticmean of the grayscale values to obtain a grayscale value of thescaled-down line image may over-corrode the coordinate values of therightmost object pixel and the leftmost object pixel, or even neglectthe endpoint object pixels. For example, if the first magnification is1/64, the grayscale values of 64 pixels are converted to 1 grayscalevalue at each time. If these 64 pixels contain object pixels, theconverted grayscale value may be larger than the grayscale thresholdvalue, and thus these 64 pixels are all determined as the backgroundpixels. For acquiring more precise coordinate values of the rightmostobject pixel and the leftmost object pixel of the line image, the rangebetween the left endpoint coordinate and the right endpoint coordinateof the would-be object pixels obtained by the first horizontallyscaling-down operation is broadened by subtracting or adding thepredetermined value according to this embodiment. In such way, thepixels that are determined as the background pixels outside the lineimage will be omitted. Afterwards, a second horizontally scaling-downoperation is performed on the line image at a second magnification. Thesecond magnification is greater than the first magnification. As aconsequence, the object pixels can be judge more precisely whilereducing the computing amount of the multifunction peripheral.

In the practical application, the image cropping process of the presentinvention may be implemented by a firmware that is installed in amultifunction peripheral. Since the real-time image cropping process ofthe present invention is added to the image processing method of themultifunction peripheral, the position of the object image zone in theband image can be effectively realized and the spots' image can beeliminated. Since the object image zone in the band image is effectivelycropped during the image processing method is implemented, the time ofprinting the document is reduced. Moreover, since the original image isprocessed on a band image basis and only the object image zone isprocessed without the need of processing the background zone, thecapacity of the dynamic memory required in the printing process issaved. Even if the system resource and the memory of the multifunctionperipheral are limited, the image cropping process of the presentinvention can enhance the performance of the multifunction peripheral.

While the invention has been described in terms of what is presentlyconsidered to be the most practical and preferred embodiments, it is tobe understood that the invention needs not be limited to the disclosedembodiment. On the contrary, it is intended to cover variousmodifications and similar arrangements included within the spirit andscope of the appended claims which are to be accorded with the broadestinterpretation so as to encompass all such modifications and similarstructures.

1. An image cropping process of a multifunction peripheral, saidmultifunction peripheral being configured to scan a document to acquirean original image and print said original image, said original imagecomprising an object image, said original image being segmented intoplural band images, each of said band images comprising plural lineimages, said image cropping process comprising steps of: (A) reading aband image of said original image; (B) judging whether a top edgeendpoint coordinate of said object image is included in said read bandimage by sub-steps of: (B1) searching a first line image containing saidobject image from said read band image, and calculating two objectendpoint coordinates of said first line image containing said objectimage; (B2) successively judging whether all of next plural line imagesof said first line image contain said two object endpoint coordinates;(B3) judging whether a width between two object endpoint coordinates ofat least one line image of said next plural line images is greater thana preset width value, wherein if all of said judging conditions of saidsteps (B1), (B2) and (B3) are satisfied, each of said two objectendpoint coordinates of said first line image is determined as said topedge endpoint coordinate, wherein if one of said judging conditions ofsaid steps (B1), (B2) and (B3) is unsatisfied, said steps (A) and (B)are repeatedly performed until said top edge endpoint coordinate isdetermined; (C) calculating object endpoint coordinates of all lineimages following said plural line images of said band image; (D)outputting said object endpoint coordinate having the minimum X-axiscoordinate value and said object endpoint coordinate having the maximumX-axis coordinate value among all object endpoint coordinates of saidband image; (E) receiving said object endpoint coordinates outputted insaid step (D) for further performing a printing processing operation;(F) reading a next band image, and searching all object endpointcoordinates of all line images of said next band image; (G) outputtingsaid object endpoint coordinate having the minimum X-axis coordinatevalue and said object endpoint coordinate having the maximum X-axiscoordinate value among all object endpoint coordinates of said next bandimage; (H) receiving said object endpoint coordinates outputted in saidstep (H) for further performing said printing processing operation; and(I) repeatedly performing said steps (F), (G) and (H).
 2. The imagecropping process according to claim 1 wherein said step (B1) comprisessub-steps of: (B1-1) reading a line image of said band image, andperforming a Gamma correction on said line image, wherein said lineimage comprises plural pixels; (B1-2) judging whether said pixels ofsaid line image contain said object image by horizontally scaling downsaid line image at a magnification to acquire a scaled-down line image,comparing grayscale values of respective pixels of said scaled-down lineimage with a grayscale threshold value to determine said pixel whosegrayscale value is lower than said grayscale threshold value as anobject pixel, and recording coordinates values of a leftmost objectpixel and a rightmost object pixel of said object pixels of saidscaled-down line image; and (B1-3) performing a pixel coordinatetransformation by respectively transforming said coordinates values ofsaid leftmost object pixel and said rightmost object pixel of saidobject pixels of said scaled-down line image into coordinates values ofa leftmost object pixel and a rightmost object pixel of said objectpixels of said line image, and recording said coordinates values of saidleftmost object pixel and said rightmost object pixel of said objectpixels of said line image as said two object endpoint coordinates. 3.The image cropping process according to claim 2 wherein said grayscalethreshold value W(n+1) is calculated by the following equation:W(n+1)=W(n)+(W(n+1)max−W(n))/T where, n=0, 1, 2, . . . , (A-1), W(0) isan initial grayscale value, W(n) is an accumulated reference grayscalevalue of the n^(th) line image, W(n+1)max indicates the maximumgrayscale value among all pixels of the (n+1)^(th) scaled-down lineimage that is obtained by horizontally scaling down the (n+1)^(th) lineimage at a magnification, and T and A are positive integers.
 4. Theimage cropping process according to claim 3 wherein if W(n+1)max ishigher than W(n), T=Td, and if W(n+1)max is lower than W(n), T=Tu,wherein Tu and Td are different positive integers.
 5. The image croppingprocess according to claim 1 wherein said step (B1) comprises sub-stepsof: (B1-1) reading a line image of said band image, and performing aGamma correction on said line image, wherein said line image comprisesplural pixels; (B1-2) judging whether said pixels of said line imagecontain said object image by: horizontally scaling down said line imageat a first magnification to acquire a first scaled-down line image;comparing grayscale values of respective pixels of said firstscaled-down line image with a grayscale threshold value to determinesaid pixel whose grayscale value is lower than said grayscale thresholdvalue as a would-be object pixel, and recording coordinates values of aleftmost would-be object pixel and a rightmost would-be object pixel ofsaid would-be object pixels of said first scaled-down line image;subtracting a predetermined value from a X-axis coordinate value of saidleftmost would-be object pixel of said first scaled-down line image toacquire a left reference coordinate, and adding said predetermined valueto a X-axis coordinate value of said rightmost would-be object pixel toacquire a right reference coordinate; and respectively transforming saidleft reference coordinate and said right reference coordinate into aleftmost reference coordinate and a rightmost reference coordinate ofsaid line image, horizontally scaling down said line image between saidleftmost reference coordinate and said rightmost reference coordinate ata second magnification to acquire a second scaled-down line image,comparing grayscale values of respective pixels of said secondscaled-down line image with said grayscale threshold value to determinesaid pixel whose grayscale value is lower than said grayscale thresholdvalue as an object pixel, and recording coordinates values of a leftmostobject pixel and a rightmost object pixel of said second scaled-downline image, wherein said second magnification is greater than said firstmagnification; and (B1-3) performing a pixel coordinate transformationby respectively transforming said coordinates values of said leftmostobject pixel and said rightmost object pixel of said second scaled-downline image into coordinates values of a leftmost object pixel and arightmost object pixel of said object pixels of said line image, andrecording said coordinates values of said leftmost object pixel and saidrightmost object pixel of said object pixels of said line image as saidtwo object endpoint coordinates.
 6. The image cropping process accordingto claim 5 wherein said grayscale threshold value W(n+1) is calculatedby the following equation:W(n+1)=W(n)+(W(n+1)max−W(n))/T where, n=0, 1, 2, . . . , (A-1), W(0) isan initial grayscale value, W(n) is an accumulated reference grayscalevalue of the n^(th) line image, W(n+1)max indicates the maximumgrayscale value among all pixels of the (n+1)^(th) scaled-down lineimage that is obtained by horizontally scaling down the (n+1)^(th) lineimage at a magnification, and T and A are positive integers.
 7. Theimage cropping process according to claim 6 wherein if W(n+1)max ishigher than W(n), T=Td, and if W(n+1)max is lower than W(n), T=Tu,wherein Tu and Td are different positive integers.
 8. The image croppingprocess according to claim 1 wherein said step (F) comprises sub-stepsof: (F-1) reading a line image of said next band image, and performing aGamma correction on said line image, wherein said line image comprisesplural pixels; (F-2) judging whether said pixels of said line imagecontain said object image by horizontally scaling down said line imageat a magnification to acquire a scaled-down line image, comparinggrayscale values of respective pixels of said scaled-down line imagewith a grayscale threshold value to determine said pixel whose grayscalevalue is lower than said grayscale threshold value as an object pixel,and recording coordinates values of a leftmost object pixel and arightmost object pixel of said object pixels of said scaled-down lineimage; and (F-3) performing a pixel coordinate transformation byrespectively transforming said coordinates values of said leftmostobject pixel and said rightmost object pixel of said object pixels ofsaid scaled-down line image into coordinates values of a leftmost objectpixel and a rightmost object pixel of said object pixels of said lineimage, and recording said coordinates values of said leftmost objectpixel and said rightmost object pixel of said object pixels of said lineimage as said two object endpoint coordinates.
 9. The image croppingprocess according to claim 8 wherein said grayscale threshold valueW(n+1) is calculated by the following equation:W(n+1)=W(n)+(W(n+1)max−W(n))/T where, n=0, 1, 2, . . . , (A-1), W(0) isan initial grayscale value, W(n) is an accumulated reference grayscalevalue of the n^(th) line image, W(n+1)max indicates the maximumgrayscale value among all pixels of the (n+1)^(th) scaled-down lineimage that is obtained by horizontally scaling down the (n+1)^(th) lineimage at a magnification, and T and A are positive integers.
 10. Theimage cropping process according to claim 9 wherein if W(n+1)max ishigher than W(n), T=Td, and if W(n+1)max is lower than W(n), T=Tu,wherein Tu and Td are different positive integers.
 11. The imagecropping process according to claim 1 wherein said step (F) comprisessub-steps of: (F-1) reading a line image of said next band image, andperforming a Gamma correction on said line image, wherein said lineimage comprises plural pixels; (F-2) judging whether said pixels of saidline image contain said object image by: horizontally scaling down saidline image at a first magnification to acquire a first scaled-down lineimage; comparing grayscale values of respective pixels of said firstscaled-down line image with a grayscale threshold value to determinesaid pixel whose grayscale value is lower than said grayscale thresholdvalue as a would-be object pixel, and recording coordinates values of aleftmost would-be object pixel and a rightmost would-be object pixel ofsaid would-be object pixels of said first scaled-down line image;subtracting a predetermined value from a X-axis coordinate value of saidleftmost would-be object pixel of said first scaled-down line image toacquire a left reference coordinate, and adding said predetermined valueto a X-axis coordinate value of said rightmost would-be object pixel toacquire a right reference coordinate; and respectively transforming saidleft reference coordinate and said right reference coordinate into aleftmost reference coordinate and a rightmost reference coordinate ofsaid line image, horizontally scaling down said line image between saidleftmost reference coordinate and said rightmost reference coordinate ata second magnification to acquire a second scaled-down line image,comparing grayscale values of respective pixels of said secondscaled-down line image with said grayscale threshold value to determinesaid pixel whose grayscale value is lower than said grayscale thresholdvalue as an object pixel, and recording coordinates values of a leftmostobject pixel and a rightmost object pixel of said second scaled-downline image, wherein said second magnification is greater than said firstmagnification; and (B1-3) performing a pixel coordinate transformationby respectively transforming said coordinates values of said leftmostobject pixel and said rightmost object pixel of said second scaled-downline image into coordinates values of a leftmost object pixel and arightmost object pixel of said object pixels of said line image, andrecording said coordinates values of said leftmost object pixel and saidrightmost object pixel of said object pixels of said line image as saidtwo object endpoint coordinates.
 12. The image cropping processaccording to claim 11 wherein said grayscale threshold value W(n+1) iscalculated by the following equation:W(n+1)=W(n)+(W(n+1)max−W(n))/T where, n=0, 1, 2, . . . , (A-1), W(0) isan initial grayscale value, W(n) is an accumulated reference grayscalevalue of the n^(th) line image, W(n+1)max indicates the maximumgrayscale value among all pixels of the (n+1)^(th) scaled-down lineimage that is obtained by horizontally scaling down the (n+1)^(th) lineimage at a magnification, and T and A are positive integers.
 13. Theimage cropping process according to claim 12 wherein if W(n+1)max ishigher than W(n), T=Td, and if W(n+1)max is lower than W(n), T=Tu,wherein Tu and Td are different positive integers.